Structural optimization by solving CSP via metaheuristic algorithm.

The first way, which is still commonly employed by most structural design specialists, is the Edisonian approach. The Edisonian approach to invention is defined by trial and error discovery rather than a systematic theoretical process. This necessity to have a more efficient design procedure, which means structure much closer to the optimum and in less time, led to automating the design iteration procedure. The methods used for reaching the best solution in an automated way are called Optimization methods. A significant first classification of the optimization methodologies is between Hard Computing techniques and Soft Computing (SC) techniques. Hard Computing procedures are the ones that are based on rigorous mathematical, sequential and analytical models. The SC methods don't reach an exact optimum but the near-best solution with a tolerable imprecision. Examples of SC procedures are all the metaheuristic algorithms that imitate some natural pattern. The current thesis aims to develop a cost minimization referred directly to the material stock. The optimization of the stock material was performed through the solution of the Cutting Stock Problem (CSP). The entire cost optimization was solved with the aid of a metaheuristic algorithm.